代理人工智能买家指南：如何评估企业级采购和供应链代理人工智能

Executive Summary Procurement and supply chain teams operate underincreasing pressure: shifting demand, volatile costs,supply disruptions, regulatory scrutiny, and the need tomake faster decisions with fewer resources. Traditional As a result, organizations still rely heavily on manualintervention, disconnected workflows, and reactive Agentic AI closes this gap by enabling systems thatcan reason, decide, and act based on domain-specificunderstanding. Instead of supporting tasks, intelligentagents collaborate with people to execute entireworkflows, resolving exceptions, applying policies, Why Agentic AI Matters Now Although procurement and supply chain teams may have adopted modernplatforms, much of the daily work remains: •manual and repetitive •dependent on rule-based or manual routing•slowed by bottlenecks and approvals•spread across disconnected systems•informed by inconsistent or incomplete data•vulnerable to errors, delays, and visibility gaps These issues persist because traditional automation can standardize tasks butcannot interpret nuance, resolve exceptions, or coordinate work end-to-end. Agentic AI addresses these limitations by enabling systems that plan, decide, andact within defined guardrails, continuously optimizing execution while managing •dynamic workflow in real-time orchestration •continuous optimization of processes and outcomes •flexibility •scalability •transparency •much better customer experience •faster cycle times •fewer handoffs and delays •reduced operational and compliance risk, with stronger auditability •improved decision quality •more time for strategic work •greater resilience during disruption This shift is foundational for enterprises pursuing autonomy, optimization, andresilience across procurement and supply chain operations. What Agentic AI Should Deliver Agentic AI is much more than an assistant or embedded intelligence. Modern,enterprise-ready systems should deliver five core capabilities: Autonomous Decision-Making Agents interpret context, apply business rules, evaluate constraints, and eitherrecommend or execute actions based on domain-specific understanding rather End-to-End Orchestration Agents coordinate work across sourcing, categories, contracting, buying,suppliers, risk, and planning, eliminating manual routing and ensuring consistent Real-Time Adaptation Agents adjust to changing demand, supplier issues, risk signals, and marketconditions. This can include escalation, reprioritization, or re-planning without Continuous Learning Agents improve and optimize through outcomes, user feedback, and exposure tonew data. Enterprise-Level Scalability and Governance Agents must operate at scale with embedded governance, security, auditability,and policy controls, including guardrails such as permissions, approval How Agentic AI Works Agentic AI platforms vary in maturity, but buyers evaluating enterprise-readysystems should expect certain architectural patterns that enable autonomousexecution. These typically include three layers that work together to support Assistant Layer1. A single conversational interface that spans sourcing, contracting, buying,suppliers, and risk. Users can ask questions, request actions, or initiate work fromone place, rather than navigating multiple systems or workflows. This interactionmodel helps users transition from traditional, structured interfaces such as Orchestration Layer A network of autonomous agents that collaborate to complete multi-step tasks.These agents apply business rules, resolve exceptions, coordinate across Extensibility Layer Tools that allow teams to build new agents or adapt existing ones for specificdomains, categories, regions or workflows, including agents that can operateacross an enterprise ecosystem of systems and data sources. This ensures the How the Pieces Fit Together The assistant layer interprets intent, the orchestration layer carries out the work,and the extensibility layer enables continuous adaptation. Combined, these layers What Agentic AI Is Not Agentic AI is often confused with other forms of enterprise automation. Toevaluate platforms effectively, it is important to distinguish agentic systems from Agentic AI is not: •a chatbot or conversational assistant that only retrieves information•a workflow engine that automates predefined steps True agentic AI goes beyond assistance or task automation. It enables intelligentagents to interpret context, collaborate and execute work autonomously within Agentic AI Maturity Framework Organizations evaluating AI platforms often encounter a wide range ofcapabilities, from simple assistants to systems that can execute complex work Level 1 — Assisted Intelligence AI provides recommendations, answers questions, and summarizes information.These systems support users but rely on people to make decisions, route work, Level 2 — Coordinated Intelligence AI enhances workflow automation by interpreting intent, applyin